code: def try_import_tf(error: bool = False):
      """Tries importing tf and returns the module (or None).
  
      Args:
          error: Whether to raise an error if tf cannot be imported.
  
      Returns:
          Tuple containing
          1) tf1.x module (either from tf2.x.compat.v1 OR as tf1.x).
          2) tf module (resulting from `import tensorflow`). Either tf1.x or
          2.x. 3) The actually installed tf version as int: 1 or 2.
  
      Raises:
          ImportError: If error=True and tf is not installed.
      """
      tf_stub = _TFStub()
      # Make sure, these are reset after each test case
      # that uses them: del os.environ["RLLIB_TEST_NO_TF_IMPORT"]
      if "RLLIB_TEST_NO_TF_IMPORT" in os.environ:
          logger.warning("Not importing TensorFlow for test purposes")
          return None, tf_stub, None
  
      if "TF_CPP_MIN_LOG_LEVEL" not in os.environ:
          os.environ["TF_CPP_MIN_LOG_LEVEL"] = "3"
  
      # Try to reuse already imported tf module. This will avoid going through
      # the initial import steps below and thereby switching off v2_behavior
      # (switching off v2 behavior twice breaks all-framework tests for eager).
      was_imported = False
      if "tensorflow" in sys.modules:
          tf_module = sys.modules["tensorflow"]
          was_imported = True
  
      else:
          try:
              import tensorflow as tf_module
          except ImportError:
              if error:
                  raise ImportError(
                      "Could not import TensorFlow! RLlib requires you to "
                      "install at least one deep-learning framework: "
                      "`pip install [torch|tensorflow|jax]`."
                  )
              return None, tf_stub, None
  
      # Try "reducing" tf to tf.compat.v1.
      try:
          tf1_module = tf_module.compat.v1
          tf1_module.logging.set_verbosity(tf1_module.logging.ERROR)
          if not was_imported:
              tf1_module.disable_v2_behavior()
              tf1_module.enable_resource_variables()
          tf1_module.logging.set_verbosity(tf1_module.logging.WARN)
      # No compat.v1 -> return tf as is.
      except AttributeError:
          tf1_module = tf_module
  
      if not hasattr(tf_module, "__version__"):
          version = 1  # sphinx doc gen
      else:
          version = 2 if "2." in tf_module.__version__[:2] else 1
  
      return tf1_module, tf_module, version
  
imports: import logging
  import numpy
  import os
  import sys
  from typing import Any, Optional
  from ray.rllib.utils.annotations import DeveloperAPI, PublicAPI
  from ray.rllib.utils.deprecation import Deprecated
  from ray.rllib.utils.typing import TensorShape, TensorType
label_desc: Use image node_id 2 for calling a global function with example usage: try_import_tf(error) and returns: tf1_module,  tf_module,  version, None,  tf_stub,  None, None,  tf_stub,  None